2 resultados para Online measures

em CaltechTHESIS


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Consider the Royden compactification R* of a Riemannian n-manifold R, Γ = R*\R its Royden boundary, Δ its harmonic boundary and the elliptic differential equation Δu = Pu, P ≥ 0 on R. A regular Borel measure mP can be constructed on Γ with support equal to the closure of ΔP = {q ϵ Δ : q has a neighborhood U in R* with UʃᴖRP ˂ ∞ }. Every enegy-finite solution to u (i.e. E(u) = D(u) + ʃRu2P ˂ ∞, where D(u) is the Dirichlet integral of u) can be represented by u(z) = ʃΓu(q)K(z,q)dmP(q) where K(z,q) is a continuous function on Rx Γ . A P~E-function is a nonnegative solution which is the infimum of a downward directed family of energy-finite solutions. A nonzero P~E-function is called P~E-minimal if it is a constant multiple of every nonzero P~E-function dominated by it. THEOREM. There exists a P~E-minimal function if and only if there exists a point in q ϵ Γ such that mP(q) > 0. THEOREM. For q ϵ ΔP , mP(q) > 0 if and only if m0(q) > 0 .

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Time, risk, and attention are all integral to economic decision making. The aim of this work is to understand those key components of decision making using a variety of approaches: providing axiomatic characterizations to investigate time discounting, generating measures of visual attention to infer consumers' intentions, and examining data from unique field settings.

Chapter 2, co-authored with Federico Echenique and Kota Saito, presents the first revealed-preference characterizations of exponentially-discounted utility model and its generalizations. My characterizations provide non-parametric revealed-preference tests. I apply the tests to data from a recent experiment, and find that the axiomatization delivers new insights on a dataset that had been analyzed by traditional parametric methods.

Chapter 3, co-authored with Min Jeong Kang and Colin Camerer, investigates whether "pre-choice" measures of visual attention improve in prediction of consumers' purchase intentions. We measure participants' visual attention using eyetracking or mousetracking while they make hypothetical as well as real purchase decisions. I find that different patterns of visual attention are associated with hypothetical and real decisions. I then demonstrate that including information on visual attention improves prediction of purchase decisions when attention is measured with mousetracking.

Chapter 4 investigates individuals' attitudes towards risk in a high-stakes environment using data from a TV game show, Jeopardy!. I first quantify players' subjective beliefs about answering questions correctly. Using those beliefs in estimation, I find that the representative player is risk averse. I then find that trailing players tend to wager more than "folk" strategies that are known among the community of contestants and fans, and this tendency is related to their confidence. I also find gender differences: male players take more risk than female players, and even more so when they are competing against two other male players.

Chapter 5, co-authored with Colin Camerer, investigates the dynamics of the favorite-longshot bias (FLB) using data on horse race betting from an online exchange that allows bettors to trade "in-play." I find that probabilistic forecasts implied by market prices before start of the races are well-calibrated, but the degree of FLB increases significantly as the events approach toward the end.